context-engineering-broader-than-prompt-engineering
IN premise — entries/2026/06/21/wiki-Prompt_engineering-chunk-1.md
Created 2026-06-21T09:50:10+00:00
Context engineering is the broader software engineering discipline managing all context supplied to a model: system instructions, metadata, API tools, tokens, conversation summaries, and task metadata, with practices including token budgeting, provenance tags, versioning, and observability
Summary
Managing what a language model actually receives is a full software engineering discipline, not just the act of writing a good prompt. It means treating the model's entire input window — instructions, tools, summaries, metadata — like a production system that needs budgeting, versioning, and monitoring, rather than treating each interaction as a one-off text string.
Dependents
These beliefs depend on this one:
- OUT context-engineering-enables-reliable-llm-deployment — Context engineering — managing system instructions, retrieval context, token budgets, and provenance — provides a reliable methodology for deploying LLMs with consistent, controllable behavior.